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Knowledge Networks and Markets in the Life Sciences

image of Knowledge Networks and Markets in the Life Sciences

Around the OECD countries and beyond, there is a proliferation of initiatives in the life sciences to bring together disperse elements of global research and establish an effective virtual infrastructure for open innovation. Their common goal is to leverage innovative capacity by creating interconnected webs of knowledge and exploiting external expertise.

Some such initiatives have as their goal the monetisation and trading of knowledge in the form of intellectual assets. Others seek to create networks for pooling and exchange of knowledge. Together, these initiatives can be referred to as “knowledge networks and markets” (KNMs). This report considers the development of such KNMs and examines the impact of current initiatives and the possible options for governments, working with the private sector, to improve innovation efficiency and effectiveness.

Improving the interoperability of knowledge resources is fundamental to  the creation of a necessary shared infrastructure for efficient KNM to emerge, as is related sustainable funding and policy clarity. Governments can play a vital catalytic role in improving the productivity of KNMs through such infrastructure development and encouragement of associated social networking. the report makes suggestions for some priority actions based on existing case studies.    

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Theories for building knowledge networks and markets

This chapter discusses.. how advances in information technologies are informing the design of knowledge networks and markets (KNMs), drawing heavily on experiences and insights from the ICT sector before applying some of the concepts from that sector to KNMs in biomedicine. The chapter first describes how, theoretically, knowledge markets are structured and function, and how some market failures could be overcome through better mechanism design. The chapter then discusses the importance of interoperability of separate data resources in biomedicine, and how to make these resources more interoperable and useful to many researchers. Finally, the chapter proposes how to apply these theoretical approaches to KNMs design, and to create a framework for understanding real-world examples of KNMs in biomedicine.

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